from sklearn.tree import DecisionTreeClassifier
dtree = DecisionTreeClassifier(max_depth=10,random_state=101,\
                               max_features=None,min_samples_leaf=5)
dtree.fit(XA,yA)
yP = dtree.predict(XB)
assess(yP)